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abbassix/ComNumPNdistilBERTv1-big

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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ComNumPNdistilBERT

This model is a fine-tuned version of distilbert-base-uncased a subset (8000 samples as training and 2000 samples as validation) of the ComNum dataset. We changed every single digit on a certain position in the numeral into a special character. For example '26753' becomes '3๐„‡ 5๐„ˆ 7๐„‰ 6๐„Š 2๐„‹'. Since the order of magnitude of numerals in the test set is 6, while that of numerals in training and evaluation sets are from 0 to 5, and the fine-tuned model has never seen special character for digits of the order of magnitude of 6 (e.g., '1๐„', '6๐„' or '9๐„'), it cannot generalize well.

It achieves the following results on the evaluation set:

  • โ€”Loss: 0.0458
  • โ€”Accuracy: 0.9875

It achieves the following results on the test set:

  • โ€”Loss: 3.0438
  • โ€”Accuracy: 0.5909

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Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • โ€”learning_rate: 5e-05
  • โ€”trainbatchsize: 8
  • โ€”evalbatchsize: 8
  • โ€”seed: 42
  • โ€”optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • โ€”lrschedulertype: linear
  • โ€”num_epochs: 3.0

Training results

Training LossEpochStepValidation LossAccuracy
0.29511.010000.19000.886
0.092.020000.07010.9835
0.03823.030000.04580.9875

Framework versions

  • โ€”Transformers 4.36.2
  • โ€”Pytorch 2.1.0+cu121
  • โ€”Datasets 2.16.0
  • โ€”Tokenizers 0.15.0